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Abstract #2410

kz-GRAPPA for 3D parallel imaging with localized estimation of interpolation kernels

Steen Moeller1, Sudhir Ramanna1, Essa Yacoub1, Kamil Ugurbil1, and Mehmet Akcakaya1,2

1University of Minnesota, Minneapolis, MN, United States, 2Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States

A kz-dependent shift-variant 3D GRAPPA approach for reconstructing 2D under-sampled k-space is proposed. The method results in equal or lower g-factors compared to a conventional shift-invariant 3D kernel. In turn, this permits higher 2D ky-kz accelerations, and promises significant advantages for functional and diffusion imaging. The method is demonstrated with anatomical and diffusion imaging using thin slabs.

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